By Matthias Jarke, John Mylopoulos, Christoph Quix, Colette Rolland, Yannis Manolopoulos, Haralambos Mouratidis, Jennifer Horkoff
This publication constitutes the lawsuits of twenty sixth foreign convention on complicated info platforms Engineering, CAiSE 2014, held in Thessaloniki, Greece in June 2014. The forty-one papers and three keynotes provided have been rigorously reviewed and chosen from 226 submissions. The authorized papers have been awarded in thirteen classes: clouds and companies; requisites; product strains; standards elicitation; techniques; threat and defense; technique versions; information mining and streaming; technique mining; versions; mining occasion logs; databases; software program engineering.
Read Online or Download Advanced Information Systems Engineering: 26th International Conference, CAiSE 2014, Thessaloniki, Greece, June 16-20, 2014. Proceedings PDF
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Extra resources for Advanced Information Systems Engineering: 26th International Conference, CAiSE 2014, Thessaloniki, Greece, June 16-20, 2014. Proceedings
This is for instance the case, when new impact factors are identified as the understanding about the problem grows, or as expert’s previously implicit assumptions become more explicit. 4 Avoid Risk Accelerators: An Agenda for Humanitarian Information Management and Systems Our approach to manage information and support decision-makers who are facing wicked problems in complex environments can be summarized by answering the two questions posed in the introduction. Ad 1: Information Systems Design.
Good risk management should develop strategies to avoid patterns that may (quickly) lead to undesired consequences. As illustrated in Figure 1, system σi (in black) requires a mitigation reaction that corresponds to small changes in the environment to avoid potential large losses initiated by risk driver x. For system σj (in grey), the consequences of a small deviation are less severe. Depending on x’s development there may be more time to recognize the development and act accordingly. Ultimately, it is the aim to change a system’s behavior by exerting controls such that it is less prone to failure and substantial loss.
We start the process by identifying unfavoraable consequences or paths of development d (scenarios) that need to be avoided. Inform mation management, sensemak king and decision support are used to flag these unfavoorable paths. Since it is not possible p to manage and process information related to all possible scenarios, we focu us on those that imply the most relevant consequencess in terms of plausibility and harm of consequences. Fig. 1. Risk as a system in nherent concept that evolves with changes of the environment Risk Accelerators in Disasters 17 Figure 1 shows the evolution of the performance of a risk system σ as a function of the environment.
Advanced Information Systems Engineering: 26th International Conference, CAiSE 2014, Thessaloniki, Greece, June 16-20, 2014. Proceedings by Matthias Jarke, John Mylopoulos, Christoph Quix, Colette Rolland, Yannis Manolopoulos, Haralambos Mouratidis, Jennifer Horkoff